Neonatal Encephalopathy: Novel Phenotypes and Genotypes Identified by Genome Sequencing.

BACKGROUND AND OBJECTIVES

Neonatal encephalopathy (NE) is characterized by an abnormal level of consciousness with or without seizures in the neonatal period. It affects 1-6/1,000 live term newborns. We applied genome sequencing (GS) in term newborns with NE to investigate the underlying genetic causes.

METHODS

We enrolled term newborns according to inclusion/exclusion criteria during their Neonatal Intensive Care admission. We performed GS trio and applied bioinformatic tools. We developed pipelines for manual filters. We applied in silico prediction tools, protein 3D modeling, and functional characterization to assess the pathogenicity of variants.

RESULTS

Seventeen newborns fulfilled inclusion criteria. We identified 12 variants in 10 genes. We classified 4 variants in , , , and (previously established disease genes) as pathogenic/likely pathogenic; 7 variants in (previously established disease gene), , , , , and (5 candidate genes) as variants of uncertain significance (VUS); and one variant in as likely benign. The and copy number variants (CNVs) resulted in structural changes in protein 3D models. The functional characterization of VUS revealed disruption of SorCS2 dimer formation and confirmed its pathogenicity. The functional characterization of variants updated their characterization from VUS/likely benign to benign. The VUS resulted in a shift in 3D protein structure. We were not able to perform protein 3D modeling and functional characterization of two VUS. We are not certain whether and variants may be causative of NE in our study.

DISCUSSION

The diagnostic rate of research GS was 41% in our prospective study. We broaden the phenotypic spectrum of -associated Hogue-Janssens syndrome 1, -associated nemaline myopathy 7, and -associated oculo-facio-cardio-dental syndrome to include NE and/or neonatal seizures. We identified 3 candidate genes () that may cause NE. We believe that protein 3D modeling is an important tool to assess the pathogenicity of CNVs and may advance the discoveries of novel genetic diseases. However, functional characterization of missense variants is essential for discoveries of novel genetic diseases. It seems that GS can help identify more candidate genes compared with ES.